{"title":"ReOpen demands as public health threat: a sociotechnical framework for understanding the stickiness of misinformation.","authors":"Francesca Bolla Tripodi","doi":"10.1007/s10588-021-09339-8","DOIUrl":null,"url":null,"abstract":"<p><p>In the absence of a national, coordinated, response to COVID-19, state and local representatives had to create and enforce individualized plans to protect their constituents. Alongside the challenge of trying to curb the virus, public health officials also had to contend with the spread of false information. This problematic content often contradicted safeguards, like masks, while promoting unverified and potentially lethal treatments. One of the most active groups denying the threat of COVID is The Reopen the States Movement. By combining qualitative content analysis with ethnographic observations of public ReOpen groups on Facebook, this paper provides a better understanding of the central narratives circulating among ReOpen members and the information they relied on to support their arguments. Grounded in notions of individualism and self-inquiry, members sought to reinterpret datasets to downplay the threat of COVID and suggest public safety workarounds. When the platform tried to flag problematic content, lack of institutional trust had members doubting the validity of the fact-checkers, highlight the tight connection between misinformation and epistemology.</p>","PeriodicalId":50648,"journal":{"name":"Computational and Mathematical Organization Theory","volume":"28 4","pages":"321-334"},"PeriodicalIF":1.8000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353609/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and Mathematical Organization Theory","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10588-021-09339-8","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/8/10 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In the absence of a national, coordinated, response to COVID-19, state and local representatives had to create and enforce individualized plans to protect their constituents. Alongside the challenge of trying to curb the virus, public health officials also had to contend with the spread of false information. This problematic content often contradicted safeguards, like masks, while promoting unverified and potentially lethal treatments. One of the most active groups denying the threat of COVID is The Reopen the States Movement. By combining qualitative content analysis with ethnographic observations of public ReOpen groups on Facebook, this paper provides a better understanding of the central narratives circulating among ReOpen members and the information they relied on to support their arguments. Grounded in notions of individualism and self-inquiry, members sought to reinterpret datasets to downplay the threat of COVID and suggest public safety workarounds. When the platform tried to flag problematic content, lack of institutional trust had members doubting the validity of the fact-checkers, highlight the tight connection between misinformation and epistemology.
期刊介绍:
Computational and Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for integrating data, computational models, analysis and visualization techniques.
Various types of papers and underlying research are welcome. Papers presenting, validating, or applying models and/or computational techniques, new algorithms, dynamic metrics for networks and complex systems and papers comparing, contrasting and docking computational models are strongly encouraged. Both applied and theoretical work is strongly encouraged. The editors encourage theoretical research on fundamental principles of social behaviour such as coordination, cooperation, evolution, and destabilization. The editors encourage applied research representing actual organizational or policy problems that can be addressed using computational tools. Work related to fundamental concepts, corporate, military or intelligence issues are welcome.